Geodesic
A method for topic clustering for large science publication collections
Informacionnye tehnologii i vyčislitelnye sistemy, no. 1 (2013), pp. 33-42

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The article covers research in the field of topic clustering for large science publication collections. Demands of developing such methods are considered. The method and the algorithm for topic clustering for large science publication amounts are presented. A comparison of the proposed method with classic clustering approaches is performed.
Keywords: text clustering, lexical descriptors, text spectral index, inverted spectral index, TF, IDF, topic importance characteristic, assessment of clustering methods.
Mots-clés : text classification 
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     author = {D. A. Deviatkin and R. E. Suvorov and I. V. Sochenkov},
     title = {A method for topic clustering for large science publication collections},
     journal = {Informacionnye tehnologii i vy\v{c}islitelnye sistemy},
     pages = {33--42},
     publisher = {mathdoc},
     number = {1},
     year = {2013},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/ITVS_2013_1_a3/}
}
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D. A. Deviatkin; R. E. Suvorov; I. V. Sochenkov. A method for topic clustering for large science publication collections. Informacionnye tehnologii i vyčislitelnye sistemy, no. 1 (2013), pp. 33-42. http://geodesic.mathdoc.fr/item/ITVS_2013_1_a3/